Video image data typically contain a large amount of data. For this reason, compression coding is performed when video image data is transmitted from a transmission apparatus to a reception apparatus or when video image data is stored on a storage device.
Typical video coding standards include moving picture experts group phase 2 (MPEG-2), MPEG-4, and H. 264 MPEG-4 advance video coding (MPEG-4 AVC/H. 264). These video coding standards are being formulated by the International Organization for Standardization/International Electrotechnical Commission (ISO/IEC).
In the video coding standards, two coding schemes, namely, inter-predictive coding and intra-predictive coding are adopted. The inter-predictive coding codes an coding target picture using information of a coded picture. The intra-predictive coding codes a coding target picture using only information of the coding target picture.
A next generation video coding standard called High Efficiency Video Coding (HEVC) was formulated by the organization called Joint Collaboration Team on Video Coding (JCTVC) (see non-patent literature 1 and non-patent literature 2 described below) in January 2013. JCTVC is an organization that is jointly operated by the International Telecommunication Union Telecommunication Standardization Sector (ITU-T) and ISO/IEC.
HEVC achieves a coding efficiency twice as high as H. 264 by introducing a new filter called a sample adaptive offset (SAO) and a tool that is difficult to implement because of hardware constraints when H. 264 is used.
As an extended version of HEVC, JCTVC has formulated Screen Content Coding (SCC) that is a coding standard intended for screen content application. SCC is a coding standard that is used to efficiently code artificial video, such as a desktop screen of a personal computer (PC). SCC is expected to be a coding standard in the future that may be used to compress video transmitted from a server over the cloud.
SCC is intended to handle artificial video, such as a screen on a PC. The video serving as a compression target may include a video for medical use, and a video of a computer aided design (CAD). For this reason, SCC includes a tool that accounts for a red-green-blue (RGB) color space, and a 4:4:4 color space. These videos have a higher spatial correlation of a color component than a natural image, and the number of colors used in these videos are subject to limitation in many cases. The tool added in SCC achieves an improvement in the coding efficiency by using the features of the videos.
Typical tools added in SCC are cross component prediction (CCP), adaptive color transform (ACT), and palette coding. CCP is a technique of reducing prediction errors using a correlation between the prediction errors of color components. ACT is a technique of reducing the correlation between the color components by applying a conversion from YCoCg color space to RGB color space on a prediction error.
Examples of the related art are disclosed in non-patent literature 1, JCTVC-V1005, “High Efficiency Video Coding (HEVC) Screen Content Coding: Draft 5”, Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, October 2015, and non-patent literature 2, JCTVC-V1002, “High Efficiency Video Coding (HEVC) Test Model 16 (HM 16) Improved Encoder Description Update 4”, Joint Collaborative Team on Video Coding (JCT-VC) of ITU-T SG16 WP3 and ISO/IEC JTC1/SC29/WG11, October 2015.